Geisel Academy Teaching Bootcamp: Sources of Bias in AI for Medicine and Education

Wednesday, August 6, 2025, 5:00 PM - Sunday, August 6, 2028, 6:00 PM

AMA PRA Category 1 Credits™ (1.50 hours), CME-Designated Participation Credit (1.50 hours)

This session explores how artificial intelligence (AI) is transforming healthcare delivery and education, with a focus on ethical considerations, health equity, and bias mitigation. Through real-world examples and interactive discussion, participants will learn to critically assess the risks and benefits of AI tools, understand the sources of algorithmic bias, and promote fair, inclusive, and clinically responsible use of AI.

Presenters

Thomas Thesen, Ph.D.
Associate Professor
Department of Medical Education
Geisel School of Medicine at Dartmouth
Department of Computer Science
Dartmouth College

Frances Lim-Liberty, M.D.
Staff Physician
Department of Pediatric Endocrinology
Dartmouth Hitchcock Medical Center, Lebanon, NH

Anais Ovalle, MD, MPH
Staff Physician
Department of Infectious Diseases and International Health
Dartmouth Hitchcock Medical Center, Lebanon, NH

Download the slides HERE.

1. Identify key applications of AI in healthcare and education, including how machine learning models and large language models (LLMs) function in these domains.
2. Analyze how bias can be introduced at different stages of the AI lifecycle, including evaluating its implications for health disparities and clinical decision-making.
3. Apply principles of equity, fairness, and transparency to critically assess AI tools in real-world healthcare settings, including developing strategies to advocate for ethical and inclusive implementation.

In support of improving patient care, Dartmouth Health is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. 

American Medical Association (AMA)
Dartmouth Health designates this Enduring Material for a maximum of 1.50 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. 

All other learners may claim CME-designated participation credit. Consult your professional licensing board regarding the applicability and acceptance of CME-designated participation credit for programs certified for credit by organizations accredited by Joint Accreditation for Interprofessional Education.

Registration/Requirements for Successful Completion
You may claim credit for successful completion of this online course. In order to claim credit, you must follow these steps:

1. Click the Register tab above. If you are not logged into your account, you will need to log in. Use the Forgot Your Password? button if you need to reset your password.

2. Register for the activity.

3. Click the Content/Tests tab and then View Content to view the recording. View the entire presentation.

4. Complete the Post-Test (attestation - return to the Content/Tests tab to find it).

5. Click the Complete Evaluation button, or click My Account in the menu bar; then click Evaluations.

6. Complete and Submit the Evaluation.

Bibliographic Sources

• Casal, J. E., & Kessler, M. (2023). Can linguists distinguish between ChatGPT/AI and human writing?: A study of research ethics and academic publishing. Research Methods in Applied Linguistics, 2(3), 100068.

• Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., ... & McGrew, B. (2023). Gpt-4 technical report. arXiv preprint arXiv:2303.08774.

  McDuff, D., Schaekermann, M., Tu, T., Palepu, A., Wang, A., Garrison, J., ... & Natarajan, V. (2023). Towards accurate differential diagnosis with large language models. arXiv preprint arXiv:2312.00164.

• Welivita, A., & Pu, P. (2024). Is ChatGPT More Empathetic than Humans?. arXiv preprint arXiv:2403.05572.

• Hofmann, V., Kalluri, P. R., Jurafsky, D., & King, S. (2024). AI generates covertly racist decisions about people based on their dialect. Nature, 1-8.

Provider Contact Information
Provider contact information for questions regarding accreditation of the activity:

Center for Learning and Professional Development
ACE Office
Dartmouth Health
[email protected]

Mitigation of Relevant Financial Relationships

Dartmouth Health adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education.  Any individuals in a position to control the content of a CE activity, including planners, faculty, authors, or others are required to disclose all financial relationships with ineligible companies^.  All relevant financial relationships have been mitigated prior to the commencement of the activity.

^Ineligible Company is any entity whose primary business purpose is producing, marketing, selling, re-selling or distributing healthcare products used by or on patients.